code: def test_mindspore_conv3d(
      *,
      dtype_vals,
      on_device,
      fn_tree,
      frontend,
      test_flags,
      backend_fw,
  ):
      (
          dtype,
          vals,
          weight,
          bias,
          dilations,
          strides,
          padding,
          fc,
          pad_mode,
      ) = dtype_vals
      # ToDo: Enable gradient tests for dilations > 1 when tensorflow supports it.
      _assume_tf_dilation_gt_1(
          ivy.current_backend_str(), on_device, dilations
      )
      helpers.test_frontend_function(
          input_dtypes=dtype,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          input=vals,
          weight=weight,
          bias=bias,
          stride=strides,
          padding=padding,
          dilation=dilations,
          groups=fc,
          pad_mode=pad_mode,
      )
  
imports: from hypothesis import strategies
  import pytest
  import math
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_nn.test_layers import _assume_tf_dilation_gt_1
  import ivy
label_desc: Use image node_id 11 for calling a global function with example usage: test_mindspore_conv3d() without return types